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cs.CV2026
On the Reliability of Cue Conflict and Beyond
Pum Jun Kim, Seung-Ah Lee, Seongho Park +2
Understanding how neural networks rely on visual cues offers a human-interpretable view of their internal decision processes. The cue-conflict benchmark has been influential in pro…
cs.CV2026
LIFT and PLACE: A Simple, Stable, and Effective Knowledge Distillation Framework for Lightweight Diffusion Models
Hyunsoo Han, Sangyeop Yeo, Jaejun Yoo
We demonstrate that in knowledge distillation for diffusion models, the teacher network's highly complex denoising process - stemming from its substantially larger capacity - poses…
cs.CV2025
Understanding Flatness in Generative Models: Its Role and Benefits
Taehwan Lee, Kyeongkook Seo, Jaejun Yoo +1
Flat minima, known to enhance generalization and robustness in supervised learning, remain largely unexplored in generative models. In this work, we systematically investigate the…